Figures & data
Figure 1. In each recruitment cycle, new users of drug A and new users of drug B are included and added to the cohort to continuously increase the study sample size.
![Figure 1. In each recruitment cycle, new users of drug A and new users of drug B are included and added to the cohort to continuously increase the study sample size.](/cms/asset/d95fd5b9-f6cf-4349-9dce-87f1f41556b0/iups_a_1550454_f0001_c.jpg)
Figure 3. Standardized differences in baseline covariates between new users of drug A and new users of drug B before and after adjusting on the propensity score. A standardized difference <0.1 indicates negligible imbalance.
![Figure 3. Standardized differences in baseline covariates between new users of drug A and new users of drug B before and after adjusting on the propensity score. A standardized difference <0.1 indicates negligible imbalance.](/cms/asset/205abdb7-a852-4c6d-8391-f8b111ceb5b8/iups_a_1550454_f0003_c.jpg)
Figure 4. Evaluation of how powerful an unmeasured confounder would have to be to change the observed results. For example, if the prevalence of a potential unmeasured confounder is 40% in the drug A group (x-axis) and 10% in the drug B group, then the unmeasured confounder must have a risk estimate (hazard ratio) of the outcome close to 3 to fully explain the advantage of drug A over drug B.
![Figure 4. Evaluation of how powerful an unmeasured confounder would have to be to change the observed results. For example, if the prevalence of a potential unmeasured confounder is 40% in the drug A group (x-axis) and 10% in the drug B group, then the unmeasured confounder must have a risk estimate (hazard ratio) of the outcome close to 3 to fully explain the advantage of drug A over drug B.](/cms/asset/40f157f9-fa50-4e7d-b869-1b1c14965df1/iups_a_1550454_f0004_b.jpg)